144 results about "Visual methods" patented technology

The invention discloses a visual SLAM (simultaneous localization and mapping) method based on SINS (strapdown inertial navigation system) / GPS (global positioning system) and speedometer assistance. The method comprises the following steps: when GPS signals are available, performing data fusion on output information of the GPS and the SINS to obtain information including attitudes, speeds, positions and the like; when the GPS signals are unavailable, performing data fusion on output information of a speedometer and the SINS to obtain information including attitudes, speeds, positions and the like; shooting environmental images by using a binocular camera, and performing feature extraction and feature matching on the environmental images; and achieving positioning and map building by using the obtained transcendental attitude, speed and position information and environmental features, thereby completing a visual SLAM algorithm. According to the visual SLAM method disclosed by the invention, visual SLAM is assisted by using the SINA, the GPS and the speedometer, the positioning and map building under indoor and outdoor environments can be achieved, the application range is wide, and the precision and robustness of positioning can be improved.

The invention discloses a visual SLAM method based on point-line fusion, and the method comprises the steps: firstly inputting an image, predicting the pose of a camera, extracting a feature point ofthe image, and estimating and extracting a feature line through the time sequence information among a plurality of visual angles; and matching the feature points and the feature lines, tracking the features in front and back frames, establishing inter-frame association, optimizing the pose of the current frame, and optimizing the two-dimensional feature lines to improve the integrity of the feature lines; judging whether the current key frame is a key frame or not, if yes, adding the key frame into the map, updating three-dimensional points and lines in the map, performing joint optimization on the current key frame and the adjacent key frame, and optimizing the pose and three-dimensional characteristics of the camera;and removing a part of external points and redundant key frames; and finally, performing loopback detection on the key frame, if the current key frame and the previous frame are similar scenes, closing loopback, and performing global optimization once to eliminate accumulated errors. Under an SLAM system framework based on points and lines, the line extraction speed and the feature line integrity are improved by utilizing the sequential relationship of multiple view angle images, so that the pose precision and the map reconstruction effect are improved.

The invention belongs to the technical field of unmanned driving, discloses a visual inertial navigation fusion SLAM method based on Runge-Kutta4 improved pre-integration, and is used for solving thetechnical problems of low positioning precision, poor robustness and the like of an existing visual ORB-SLAM2 method in occasions of rapid movement, sparse environmental characteristics and the like.The method comprises the following steps: inputting binocular image pair information; inputting IMU information; preprocessing the binocular image; carrying out pre-integration on the IMU by utilizinga RungeKutta4 algorithm; initializing a system; estimating joint state; locally optimizing a sliding window; and carrying out loop detection and global pose graph optimization. According to the method, positioning estimation and map creation can be effectively carried out in scenes with different difficulty levels, and compared with an original visual ORB-SLAM2 method, the method has higher positioning precision and can be applied to the technical fields of unmanned system navigation, virtual reality and the like.

The invention relates to a finger tip point extraction method based on a pixel classifier and ellipse fitting. A coordinate of a palm point provided by OpenNI (open type natural interaction) is employed to segment a hand area, a Bayes skin color model is employed to remove non-skin-color areas, and the hand area is accurately extracted; and the pixel classifier is defined for the clustering of finger areas, the contour of the finger areas is extracted, the least squares method is employed for ellipse fitting, and the point of two endpoints of the long axis of the ellipse, furthest away from the palm point, is the finger tip point. The method is advantageous in that finger tip points are accurately detected in real time based on a visual-only method, and compared with data glove and color glove methods, the method is more natural and comfortable.

A Head-Mounted Display system together with associated techniques for performing accurate and automatic inside-out positional, user body and environment tracking for virtual or mixed reality are disclosed. The system uses computer vision methods and data fusion from multiple sensors to achieve real-time tracking. High frame rate and low latency is achieved by performing part of the processing on the HMD itself.

A lens aid, lens aid system and powered light source combined with a mirror that uses a lens cup of soft pliable material providing an improved visual method including a hands-free or one hand method for the insertion of a contact lens and more preferably a scleral lens into the eye.